# 5.6 Adapt the brief to the task type (/managing-ai-workers/the-four-part-brief/task-type)

---
type: Document
title: "5.6 Adapt the brief to the task type"
description: "What to set tightly and what to leave open for research, analysis, drafting, extraction and brainstorming."
status: stable
order: 205.6
ksor:
  owner: team:panaversity
  audience: [ public ]
  approval:
    by: process:panaversity
    at: 2026-10-06T13:16:37Z
chapter: "05"
part: II
expert_status: required
concepts: [ "5.6" ]
last_verified: 2026-10-06
sources:
  - id: v1-ai-prompting
    title: "AI Prompting in 2026 (Panaversity, first edition, verified 2026-10-06)"
    resource: https://agentfactory.panaversity.org/docs/ai-prompting-2026
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  at: 2026-10-06T13:16:37Z
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---

**In everyday life.** Asking friends for vacation ideas is different from booking the flight you chose.

**At work.** Asking for ways to avoid late fees needs a loose brief. Pulling the fields out of invoices needs the tightest one.

The four parts never change. How tightly you set them does. A tight brief fixes exactly what the answer must look like. A loose one leaves room for the worker's own ideas. Either way, give the worker the context, limits and sources the task needs, every time. Only the shape of the answer gets tighter or looser.

| Task type | Tighten | Leave open | If you do the opposite |
| --- | --- | --- | --- |
| Research | Scope (what to cover), source types, dates | The answer | Your own assumptions, handed back to you |
| Analysis | The data, the definitions, the exact question | The conclusion | An analysis that just agrees with the question |
| Drafting | Audience, length, structure, facts, voice | Wording and order within the structure | A well-written draft of the wrong thing |
| Extraction | Every field, its type, how to mark a missing value | Nothing | Invented values that look real |
| Brainstorming | The problem, the audience, what to avoid | Structure, tone, length | Five rewordings of one idea |

Two more rules go with the table. For research and analysis, never present the conclusion you hope for as already true, because a worker that sees it tends to find it. If you have a hypothesis, a guess of your own, state it as something to test, and ask for evidence for and against.[^v1-ai-prompting] For extraction, tell the worker to leave a field blank and flag it instead of guessing. A guessed invoice number looks exactly like a real one. Technical tasks follow the same rows. Turning invoices into JSON records that a system checks is extraction at its tightest. JSON is a file format that programs read. Name the schema (the fields the system expects and the type of each), and what to return when a value is missing.

[^v1-ai-prompting]: AI Prompting in 2026, Panaversity, first edition.